ReviewTheranostics2023
Peptide-drug co-assembling: A potent armament against cancer.
Review in Theranostics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Synthesis of 1,2,3,4-Tetrahydroisoquinoline-3-Carboxylic Acid-Embedded Decapeptides: In Silico Studies and In Vitro Evaluation Against Breast Cancer.ChemistryOpen · 2026Article
- Integrin α6 Targeted Tumor Theranostics.Phenomics (Cham, Switzerland) · 2025Review
- Peptide-Drug Conjugates: A New Hope for Cancer.Journal of peptide science : an official publication of the European Peptide Society · 2025Review
- Current progress and remaining challenges of peptide-drug conjugates (PDCs): next generation of antibody-drug conjugates (ADCs)?Journal of nanobiotechnology · 2025Review
- Recent Advances in Smart Linkage Strategies for Developing Drug Conjugates for Targeted Delivery.Topics in current chemistry (Cham) · 2025Review
- Trypsin-instructed bioactive peptide nanodrugs with cascading transformations to improve chemotherapy against colon cancer.Journal of nanobiotechnology · 2025Article
- Evaluating TcAs for Use in Biotechnology Applications.Biotech (Basel (Switzerland)) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is still one of the major problems threatening human health and the therapeutical efficacies of available treatment choices are often rather low. Due to their favorable biocompatibility, simplicity of modification, and improved therapeutic efficacy, peptide-based self-assembled delivery systems have undergone significant evolution. Physical encapsulation and covalent conjugation are two common approaches to load drugs for peptide assembly-based delivery, which are always associated with drug leaks in the blood circulation system or changed pharmacological activities, respectively. To overcome these difficulties, a more elegant peptide-based assembly strategy is desired. Notably, peptide-mediated co-assembly with drug molecules provides a new method for constructing nanomaterials with improved versatility and structural stability. The co-assembly strategy can be used to design various nanostructures for cancer therapy, such as nanotubes, nanofibrils, hydrogels, and nanovesicles. Recently, these co-assembled nanostructures have gained tremendous attention for their unique superiorities in tumor therapy. This article describes the classification of assembled peptides, driving forces for co-assembly, and specifically, the design methodologies for various drug molecules in co-assembly. It also highlights recent research on peptide-mediated co-assembled delivery systems for cancer therapy. Finally, it summarizes the pros and cons of co-assembly in cancer therapy and offers some suggestions for conquering the challenges in this field.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.